The present invention relates to interference cancellation in wireless communications systems, and more particularly to interference cancellation in single antenna receivers.
In a wireless digital Time Division Multiple Access (TDMA) communication system, such as the Global System for Mobile communications (GSM) and the Enhanced Data rate for GSM Evolution (EDGE), the quality of a receiver's performance is limited by interfering signals that, when combined with an intended signal, distort that intended signal. Most interference comes from other users in the same system. The signals transmitted by users of the identical carrier frequency in a neighboring cell create Co-Channel Interferences (CCI), while users of adjacent carrier frequencies cause Adjacent-Channel Interference (ACI).
This situation is illustrated in FIG. 1, which depicts a wireless communication network 100 of the type in which the present invention may be practiced. The network 100 may be any of a number of well-known types such as, but not limited to, GSM, General Packet Radio Service (GPRS), Digital Advanced Mobile Phone System (DAMPS), and the like.
The network 100 comprises several base stations 101, 103, 105. Each base station covers three proximate areas arranged in a honeycomb-like structure as shown. Base station 101 covers proximate areas A1, A2 and A3, while base station 103 covers proximate areas C1, C2 and C3. Each base station 101, 103, 105 is able to cover three honeycomb areas by means of sectorized antennas.
It will be observed that, in FIG. 1, each of the areas is denoted by one of the letters A, B, and C, followed by one of the numbers 1, 2, and 3 (e.g., “A1”, “A2”, “A3”, “B1”, “B2”, and so on). The letters represent a group of frequencies that are allotted for use by the base station and mobile stations located within the base station's three-sector group. Different groups have different frequencies allotted to them. The numbers denote a particular sector within the three-sector group. By allotting different frequencies to neighboring three-sector groups, CCI can be avoided. In accordance with well-known frequency reuse strategies, the same group of frequencies can be allotted to more than one three-sector group so long as the distance between these groups is considered to be sufficient to minimize (but not necessarily completely eliminate) CCI between them. The pattern that dictates in which cells the same frequencies will be allotted within the system 100 is called a “reuse pattern.” Thus, FIG. 1 illustrates several different groups, each denoted A1, A2, A3; several different groups, each denoted B1, B2, B3; and several different groups, each denoted C1, C2, and C3.
In the situation illustrated in FIG. 1 the base station 105, which is allotted the same frequencies as is used by base station 101, transmits using the same channel as is used by the base station 101. As this signal has the potential to cause CCI within the three sectors served by the base station 101, this transmitted signal is denoted ICO.
A user equipment (UE) 107, which is located in the area A3 served by the base station 101, receives an intended signal S from base station 101. At the same time, the UE 107 receives the interfering signal ICO transmitted by the base station 105.
The base station 103 does not transmit using the same frequencies as are used by the base station 101. Nonetheless, its transmissions can be on frequencies that are sufficiently close to the frequencies used by the base station 101 to cause ACI. To illustrate this point in FIG. 1, the UE 107 receives an interfering signal IADJ from the base station 103. The Signals ICO and IADJ are normally weak for networks with classical frequency planning, but may be strong and cause severe problems in a more modern network with a more aggressive frequency reuse scheme.
For a number of reasons, the particular way that an interfering signal manifests itself in the intended signal will differ depending upon the location of the receiver's antenna relative to the transmitter's antenna. Known techniques involving multiple antennas or antenna arrays exploit this so-called spatial diversity for the purpose of canceling interference in radio communications. However, due to physical constraints (e.g., size) and power consumption considerations, modem mobile receivers typically have only one antenna and therefore rely on Single Antenna Interference Cancellation (SAIC) technology to reduce the effects of interference. Since SAIC has a great potential impact on the network capacity, a new standard with a tightened CCI protection is expected to be specified for a class of receiver, with so-called Downlink Advanced Receiver Performance (DARP). See 3GPP TS 45.005, “Technical Specification Group GSM/EDGE Radio Access Network; Radio Transmission and Reception”, change request, GP-042829, November, 2004 for more general background information about this topic. Thus it is of vital importance for receivers to satisfy the tougher requirement with implementation-friendly approaches.
Spatial-Temporal Whitening (STW) is a known approach for SAIC technology. This approach utilizes the fact that, in complex representation of the baseband signal, a Gaussian Minimum Shift Keying (GMSK)-modulated interference signal is 1-dimensional, and can be rejected by exploiting the spatial redundancy obtained from the real and imaginary dimensions of the complex received signal. In STW, the interference is modeled in a spatial-temporal autoregressive model, and a spatial-temporal filter is then applied to invert the process into white noise.
An aspect of STW is that spatial (or spatial-temporal) de-correlation is necessary, where a crucial operation is the Cholesky factorization of the inverted noise autocorrelation matrix:F=chol(Q−1)  (1)where Q is the noise autocorrelation matrix. There are two problems with the operation.
First, due to the fact that the real and imaginary components of the received complex signal may be partially correlated, the noise autocorrelation matrix can lose rank. In such case the inversion of the noise autocorrelation is difficult, and the computation will not be performed.
Second, the Cholesky factorization requires that the matrix be positive definite. However, this is not always the case, especially when the temporal dimension is higher (e.g., a 2nd-order whitening filter), which is sometimes required in dealing with highly temporal interference, such as ACI. When the inverse of the noise autocorrelation matrix is not positive definite, Choleskey factorization will not be performed and the algorithm may be incomputable. Even if the received signal physically satisfies the condition of Eqn (1), the mathematical operation can still be critically ill-conditioned due to various impairments, such as noise estimation error, and limited resolution in fixed-point Digital Signal Processor (DSP) implementation of the algorithms, causing the algorithm to breakdown.
It is therefore desired to provide other approaches to single antenna interference cancellation.